Web-based Experiment on Human Performance in Dual-Robot Teleoperation

In most cases, upgrading from a single-robot system to a multi-robot system comes with increases in system payload and task performance. On the other hand, many multi-robot systems in open environments still rely on teleoperation. Therefore, human performance can be the bottleneck in a teleoperated multi-robot system. Based on this idea, the multi-robot system's shared autonomy and control methods are emerging research areas in open environment robot operations. However, the question remains: how much does the bottleneck of the human agent impact the system performance in a multi-robot system? This research tries to explore the question through the performance comparison of teleoperating a single-robot system and a dual-robot system in a box-pushing task. This robot teleoperation experiment on human agents employs a web-based environment to simulate the robots' two-dimensional movement. The result provides evidence of the hardship for a single human when teleoperating with more than one robot, which indicates the necessity of shared autonomy in multi-robot systems

TeLeMan: Teleoperation for Legged Robot Loco-Manipulation using Wearable IMU-based Motion Capture

Human life is invaluable. When dangerous or life-threatening tasks need to be completed, robotic platforms could be ideal in replacing human operators. Such a task that we focus on in this work is the Explosive Ordnance Disposal. Robot telepresence has the potential to provide safety solutions, given that mobile robots have shown robust capabilities when operating in several environments. However, autonomy may be challenging and risky at this stage, compared to human operation. Teleoperation could be a compromise between full robot autonomy and human presence. In this paper, we present a relatively cheap solution for telepresence and robot teleoperation, to assist with Explosive Ordnance Disposal, using a legged manipulator (i.e., a legged quadruped robot, embedded with a manipulator and RGB-D sensing). We propose a novel system integration for the non-trivial problem of quadruped manipulator whole-body control. Our system is based on a wearable IMU-based motion capture system that is used for teleoperation and a VR headset for visual telepresence. We experimentally validate our method in real-world, for loco-manipulation tasks that require whole-body robot control and visual telepresence

Adonis: Practical and Efficient Control Flow Recovery through OS-Level Traces

Control flow recovery is critical to promise the software quality, especially for large-scale software in production environment. However, the efficiency of most current control flow recovery techniques is compromised due to their runtime overheads along with deployment and development costs. To tackle this problem, we propose a novel solution, Adonis, which harnesses OS-level traces, such as dynamic library calls and system call traces, to efficiently and safely recover control flows in practice. Adonis operates in two steps: it first identifies the call-sites of trace entries, then it executes a pair-wise symbolic execution to recover valid execution paths. This technique has several advantages. First, Adonis does not require the insertion of any probes into existing applications, thereby minimizing runtime cost. Second, given that OS-level traces are hardware-independent, Adonis can be implemented across various hardware configurations without the need for hardware-specific engineering efforts, thus reducing deployment cost. Third, as Adonis is fully automated and does not depend on manually created logs, it circumvents additional development cost. We conducted an evaluation of Adonis on representative desktop applications and real-world IoT applications. Adonis can faithfully recover the control flow with 86.8% recall and 81.7% precision. Compared to the state-of-the-art log-based approach, Adonis can not only cover all the execution paths recovered, but also recover 74.9% of statements that cannot be covered. In addition, the runtime cost of Adonis is 18.3× lower than the instrument-based approach; the analysis time and storage cost (indicative of the deployment cost) of Adonis is 50× smaller and 443× smaller than the hardware-based approach, respectively. To facilitate future replication and extension of this work, we have made the code and data publicly available

Biosynthesis of long-chain polyunsaturated fatty acids in the razor clam Sinonovacula constricta: characterization of four fatty acyl elongases and a novel desaturase capacity

As an unusual economically important aquaculture species, Sinonovacula constricta possesses high levels of long-chain polyunsaturated fatty acids (LC-PUFA). Previously, our group identified fatty acyl desaturases (Fad) with Δ5 and Δ6 activities in S. constricta, which was the first report of Δ6 Fad in a marine mollusc. Here, we further successfully characterize elongases of very long-chain fatty acids (Elovl) in this important bivalve species, including one Elovl2/5, two Elovl4 isoforms (a and b) and a novel Elovl (c) with Elovl4 activity. In addition, we also determined the desaturation activity of S. constricta Δ6 Fad toward 24:5n-3 to give 24:6n-3, a key intermediate in docosahexaenoic acid (DHA) biosynthesis. Therefore, S. constricta is the first marine mollusc reported to possess all Fad and Elovl activities required for LC-PUFA biosynthesis via the ‘Sprecher pathway’. This finding greatly increases our understanding of LC-PUFA biosynthesis in marine molluscs. Phylogenetic analysis by interrogating six marine molluscan genomes, and previously functionally characterized Elovl and Fad from marine molluscs, suggested that DHA biosynthetic ability was limited to a few species, due to the general lack of Δ4 or Δ6 Fad in most molluscs

Whole-Body Compliant Control of iCub: first results with OpenSoT

International audienc

A²ML: A general human-inspired motion language for anthropomorphic arms based on movement primitives

The recent increasing demands on accomplishing complicated manipulation tasks necessitate the development of effective task-motion planning techniques. To help understand robot movement intention and avoid causing unease or discomfort to nearby humans toward safe human–robot interaction when these tasks are performed in the vicinity of humans by those robot arms that resemble an anthropomorphic arrangement, a dedicated and unified anthropomorphism-aware task-motion planning framework for anthropomorphic arms is at a premium. A general human-inspired four-level Anthropomorphic Arm Motion Language (A²ML) is therefore proposed for the first time to serve as this framework. First, six hypotheses/rules of human arm motion are extracted from the literature in neurophysiological field, which form the basis and guidelines for the design of A²ML. Inspired by these rules, a library of movement primitives and related motion grammar are designed to build the complete motion language. The movement primitives in the library are designed from two different but associated representation spaces of arm configuration: Cartesian-posture-swivel-angle space and human arm triangle space. Since these two spaces can be always recognized for all the anthropomorphic arms, the designed movement primitives and consequent motion language possess favorable generality. Decomposition techniques described by the A²ML grammar are proposed to decompose complicated tasks into movement primitives. Furthermore, a quadratic programming based method and a sampling based method serve as powerful interfaces for transforming the decomposed tasks expressed in A²ML to the specific joint trajectories of different arms. Finally, the generality and advantages of the proposed motion language are validated by extensive simulations and experiments on two different anthropomorphic arms

The Association of Midday Napping With Hypertension Among Chinese Adults Older Than 45 Years: Cross-sectional Study

BackgroundHypertension is one of the main public health issues around worldwide, and midday napping is a popular habit. The association between the two remains to be explored. ObjectiveThe goal of the research was to explore the association of midday napping with hypertension. MethodsThis study separately selected 11,439, 12,689, and 9464 Chinese respondents aged over 45 years from the China Health and Retirement Longitudinal Study 2011, 2015, and 2018 data sets. Binary logistic regression was used to explore the association of midday napping with hypertension, and the 3-step method was used to test the mediation effect of BMI. ResultsAmong all respondents, the prevalence rates of hypertension were 24.6% (2818/11439) in 2011, 21.1% (2683/12689) in 2015, and 22.1% (2092/9464) in 2018. Midday napping was positively correlated with hypertension. In 2011 and 2015, napping 60 to 90 minutes had the greatest odds ratios [OR] (OR2011 1.705, OR2015 1.494). In 2018, the biggest OR came from the group napping 30 to 60 minutes (OR 1.223), and ORs of different napping durations decreased from 2011 to 2018. In addition, BMI had a partial mediation effect in 2015 and 2018. ConclusionsMidday napping is a potential risk factor for hypertension with BMI acting as a mediator. To prevent hypertension, avoiding prolonged duration of midday napping and taking action to maintain a normal BMI level are recommended

A Study of Nonlinear Forward Models for Dynamic Walking

You Y, Zhou C, Li Z, Tsagarakis N. A Study of Nonlinear Forward Models for Dynamic Walking. In: IEEE International Conference on Robotics and Automation (ICRA). Singapore; Accepted

Straight Leg Walking Strategy for Torque-controlled Humanoid Robots

You Y, Xin S, Zhou C, Tsagarakis N. Straight Leg Walking Strategy for Torque-controlled Humanoid Robots. In: IEEE International Conference on Robotics and Biomimetics. Qingdao, China; 2016: 2014-2019